Interpretation of stationarity tests

[ch262]

Hi There,

I'm trying to understand the implications of a transformation of data. I am looking at quarterly UK CPI data and understand that the difference of the log is a good approximation of percentage change when dealing with low changes. As such I was looking to use the difference in the log of CPI to give me the figure for inflation over that period.

My question is in regards to its order of integration.

The raw CPI data tests according to a dickey fuller test, as non-stationary.
The difference of log of CPI (inflation) tests as stationary.

The hypothesis I am working on is based upon the idea that inflation has a casual effect on another variable, not CPI itself.

If I am working with inflation (the difference of logs of CPI) in my model, and that tests as stationary, is it therefore I(0) or is it I(1) because there has been a differencing in it's manipulation (however not for the purpose of correcting for stationarity).

I look forward to any help you may be able to give me.

Regards
Chris